A.Event Level

B.Assessment Bins

C.Model Type

D.Link Function

E.Data Source

F.Response Variable

A.No partition will be used because there are more than two levels.

B.Observations with a value of 0 will be used as Training data.

C.Observations with a value of 1 will be used as Training data.

D.Observations with a value of 2 will be used as Training data.

A.Decision trees cannot handle missing values.

B.Decision trees can be used for outlier detection.

C.Decision trees cannot handle continuous dependent variables.

D.Decision trees can be used for classification and estimation.

A.A variable with a known constant coefficient

B.A predictor variable

C.A variable used to adjust the intercept

D.The target variable

A.The maximum depth of the tree

B.The minimum number of data points in a leaf node

C.The number of neighbors in a k-nearest neighbors model

D.The learning rate for gradient boosting